Instructions to use huggingtweets/nathaniacolver with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use huggingtweets/nathaniacolver with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="huggingtweets/nathaniacolver")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("huggingtweets/nathaniacolver")
model = AutoModelForCausalLM.from_pretrained("huggingtweets/nathaniacolver", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use huggingtweets/nathaniacolver with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "huggingtweets/nathaniacolver"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "huggingtweets/nathaniacolver",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/huggingtweets/nathaniacolver

SGLang

How to use huggingtweets/nathaniacolver with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "huggingtweets/nathaniacolver" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "huggingtweets/nathaniacolver",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "huggingtweets/nathaniacolver" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "huggingtweets/nathaniacolver",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use huggingtweets/nathaniacolver with Docker Model Runner:
```
docker model run hf.co/huggingtweets/nathaniacolver
```

nathaniacolver

Commit History

Jan 25, 2025

03:06
Adding `safetensors` variant of this model⁠

SFconvertbot

Verified signature
9f8377c

Apr 3, 2023

22:05
New model from https://wandb.ai/wandb/huggingtweets/runs/jab5ifpt

boris

7637d6d

Mar 8, 2023

02:06
Update model preview

boris

908e66e
02:05
New model from https://wandb.ai/wandb/huggingtweets/runs/wposg72x

boris

242bfb7

Mar 7, 2023

05:29
Update model preview

boris

fdcc984
05:13
New model from https://wandb.ai/wandb/huggingtweets/runs/bcbews1i

boris

361c01f
01:00
Update model preview

boris

bd88fab
00:58
New model from https://wandb.ai/wandb/huggingtweets/runs/emc5vm7b

boris

79b3a4a
00:58
initial commit

huggingtweets-app

40839d0

Commit History

Jan 25, 2025

Adding `safetensors` variant of this model⁠

Apr 3, 2023

New model from https://wandb.ai/wandb/huggingtweets/runs/jab5ifpt

Mar 8, 2023

Update model preview

New model from https://wandb.ai/wandb/huggingtweets/runs/wposg72x

Mar 7, 2023

Update model preview

New model from https://wandb.ai/wandb/huggingtweets/runs/bcbews1i

Update model preview

New model from https://wandb.ai/wandb/huggingtweets/runs/emc5vm7b

initial commit